import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
#import data_extract as de
global null
null = np.nan

data = pd.read_csv(r'.//AEI.csv', index_col=0)
plt.hist(data)
plt.show()



# data = pd.read_csv(r'.//input.csv', index_col=0)
# for field in ['status_second', 'inventory_type']:
#     new_chart = pd.read_csv(r'.//new_chart_'+field, index_col=0)
#     promotion_id = new_chart['promotion_id'].unique()
#     new_column_name = new_chart[field].unique()
#     new_column_name = new_column_name[~pd.isna(new_column_name)]
#     add_chart = pd.DataFrame([], columns=new_column_name, index=promotion_id)
#     for index, row in new_chart.iterrows():
#         if pd.isna(row[field]):
#             continue
#         add_chart.loc[row['promotion_id'], row[field]] = 1
#     add_chart.index = range(0, 50000)
#     add_chart = add_chart.fillna(0)
#     data = pd.concat([data, add_chart], axis=1)
#     print(1)
# data.to_csv('new_input.csv')
